| Title |
Precursor-induced conditional random fields: connecting separate entities by induction for improved clinical named entity recognition
|
|---|---|
| Published in |
BMC Medical Informatics and Decision Making, July 2019
|
| DOI | 10.1186/s12911-019-0865-1 |
| Pubmed ID | |
| Authors |
Wangjin Lee, Jinwook Choi |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 33% |
| France | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 18 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 11% |
| Student > Ph. D. Student | 2 | 11% |
| Lecturer | 1 | 6% |
| Student > Doctoral Student | 1 | 6% |
| Professor | 1 | 6% |
| Other | 3 | 17% |
| Unknown | 8 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 3 | 17% |
| Agricultural and Biological Sciences | 1 | 6% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Engineering | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 11 | 61% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 July 2019.
All research outputs
#18,025,055
of 23,152,542 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,522
of 2,016 outputs
Outputs of similar age
#242,480
of 346,206 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#39
of 43 outputs
Altmetric has tracked 23,152,542 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,016 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 346,206 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.